Topological concepts open many new horizons for photonic devices, from integrated optics to lasers. The complexity of large scale topological devices asks for an effective solution of the inverse problem: how best to engineer the topology for a specific application? We introduce a novel machine learning approach to the topological inverse problem. We train a neural network system with the band structure of the Aubry-Andre-Harper model and then adopt the network for solving the inverse problem. Our application is able to identify the parameters of a complex topological insulator in order to obtain protected edge states at target frequencies. One challenging aspect is handling the multivalued branches of the direct problem and discarding unphysical solutions. We overcome this problem by adopting a self-consistent method to only select physically relevant solutions. We demonstrate our technique in a realistic topological laser design and by resorting to the widely available open-source TensorFlow library. Our results are general and scalable to thousands of topological components. This new inverse design technique based on machine learning potentially extends the applications of topological photonics, for example, to frequency combs, quantum sources, neuromorphic computing and metrology.
We are announcing the Tailored Disorder Symposium at the MRS (Material Research Society) Fall Meeting 2018
Disorder and perturbed periodicity in materials are in the process of becoming a vital research area that has started to show that optical media do not necessarily have to be regular. Photonic materials with deliberately introduced disorder in their respective geometries and compositions show interesting novel and tunable unforeseen properties. So far, countable scientific achievements have been reported in the areas of biology, materials science, nano-optics and -photonics that, however, already point towards a wealth of interesting effects with several applicative dimensions. This notion could be derived from the finding of structural disorder being often beneficial in nature and being useful as an engineering guide for the development of novel advanced optics and photonics devices. The general subject of structural disorder is rapidly emerging into an area of interdisciplinary scientific interest, which is however still in its infancy. Therefore, the purpose of this symposium is to bring together specialists from various scientific communities such as physics, biology and materials science and engineering to advance the structural disorder research area based on fundamental and applied research with emphasis on multidisciplinary approaches and fabrication routes. Contributions from the fields of theoretical, applied and computational physics, optics and photonics in biology, materials engineering and nano-patterning are encouraged. The development of novel approaches and design routes to realize tailored disorder in materials will be one of the main topics of the symposium. Presentations might include various patterning procedures including etching techniques, replica moulding, self-assembly, sol-gel procedures, solid state synthesis, soft lithography, layer-by-layer deposition with the focus on materials functions and properties.
Symposium organizers: Cordt Zollfrank, Claudio Conti, Hui Cao, Sushil Mujumdar
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Web-Press release on graphene for 3D bone-printing
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